Statistics.com courses on RESTful APIs

Applying analytics to big data requires a mechanism to rapidly get and share data and RESTful APIs is the standard way doing it. Learn how to write Python code to ingest data, communicate with, and create RESTful APIs with online courses from Statistics.com.

Applying analytics to big data requires a mechanism to rapidly get and share data. For example: when deploying statistical or machine learning models as part of a data product, e.g. in a real-time recommender system, the consumer's initial choices, along with other information about similar consumers and similar purchase patterns, must be transmitted to the analytics algorithm. Seconds later, the algorithm's output - the recommendation - must be transmitted to the web interface to show the consumer.

Learn about the standard way of sharing and communicating data among applications and services on the internet in Statistics.com:

REST
stands for Representational State Transfer, and API for Application Programming Interface. In this course, students will learn how to write Python code to ingest data from and communicate with RESTful APIs on the web.

The instructor, Allen Leis, is a software engineer with over 15 years of experience developing web applications in a variety of domains from the Federal Government to retail. He has deep experience in the production and consumption of RESTful APIs. These APIs power single-page javascript, iOS, and Android applications for the consumption or visualization of data, and are also an important part of the fabric of data ingestion and data quality efforts.

Participants can ask questions and exchange comments directly with Allen via a private discussion board throughout the period.

We specialize in personal attention and value pricing. There are no set hours when you must be online, and we estimate you will need about 15 hours per week. This is not a 'MOOC' (massive open online course) -- enrollment is limited, and your instructor will respond to each question that you ask.